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What Gets Lost When Memory Becomes Media? Evaluating AI-Generated Oral History Visualization

arXiv:2607.24756v1 Announce Type: cross Abstract: What gets lost when memory becomes media? Diaspora oral-history interviews require a double transformation; first-person recollection to third-person

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When Algorithms Meet Artists: Semantic Compression and Stake-holder Marginalisation in Public AI-Art Discourse (2013-2025)

DGX agent

arXiv:2508.03037v5 Announce Type: replace Abstract: Artists occupy a paradoxical position in generative AI. Their own work trains models that now compete with them, replicate their styles, and reshape

applicationsarxiv-cs-cl

29 Jul 2026

When Do Agent Loops Mistake Stagnation for Progress? Self-Evaluation Bias and Externally Grounded Verification in Long-Running Autonomous LLM Agent Loops

arXiv:2607.25152v1 Announce Type: new Abstract: Long-running autonomous agents plan, act, and judge their own completion without human intervention. When an agent grades its own work, self-evaluation

When Does Deep Representation Learning Help Single-Cell Clustering? A Sensitivity-Aware Diagnostic Benchmark for Biomedical AI Pipelines

arXiv:2607.25288v1 Announce Type: new Abstract: Single-cell ribonucleic acid sequencing (scRNA-seq) is a foundational technology for precision-medicine workflows that contribute to United Nations Sust

When Does Legacy Data Start to Help? Emergent Transfer in Cross-Configuration Robot Learning

arXiv:2607.25593v1 Announce Type: new Abstract: Robotic hardware evolves over time, but demonstration data is often tied to a specific sensor and actuator configuration. This raises a practical and un

safetyarxiv-cs-ro

When Shortest Isn't Safest: A Design Science Approach to Senior-Friendly Pedestrian Routing

arXiv:2607.24795v1 Announce Type: new Abstract: Older adults' independent mobility enables out-of-home participation, well-being and health, yet pedestrian navigation systems still optimize primarily

When Thinking Before Retrieval Hurts: TraceBound Diagnostics for Adaptive Knowledge-Graph Retrieval

arXiv:2607.24800v1 Announce Type: cross Abstract: Adaptive retrieval promises to make knowledge-graph question answering more robust by letting a controller search, inspect neighborhoods, revise actio

Where Steering Signals Come From: Activation Source Selection in Activation Steering

arXiv:2607.25270v1 Announce Type: cross Abstract: Activation steering controls language models by adding vectors or features to hidden states at inference time, but the upstream source of these steeri

WHTMix: Efficient Stereo Depth Estimation via Walsh-Hadamard Token Mixing

arXiv:2607.25234v1 Announce Type: new Abstract: Stereo depth estimation for driving, robotics and augmented reality must run at high resolution under tight latency budgets, yet in transformer-based ma

Why Public Service AI Governance Frameworks Risk Failing in the Age of General-Purpose AI: Lessons from Policing

arXiv:2607.25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressur

Wonder: Video World Model Done Better

arXiv:2607.26037v1 Announce Type: new Abstract: We present Wonder, a general-purpose video world model for real-time, camera-controllable world exploration. Given an image or a conditional video, Wond

WorkSurface-Bench: Benchmarking Enterprise Agents on Multi-Surface Knowledge Routing

model-releasesarxiv-cs-cl

arXiv:2607.25765v1 Announce Type: new Abstract: Enterprise agents often need to integrate heterogeneous knowledge sources: documents for narrative facts, tables for computation, and dependency graphs

Zhinv: Real-time hub-height wind field reconstruction using only local sparse observations

arXiv:2607.25298v1 Announce Type: new Abstract: The high proportion of wind power connected to the grid places higher demands on fine-grained knowledge of regional wind fields. Since the wind informat

researcharxiv-cs-lg

A Case Study on the Acceptance of a Humanoid Robotic Head Employed in Three Public Spaces

arXiv:2607.24113v1 Announce Type: cross Abstract: Previous research has shown that a human-like robot's acceptance heavily depends on the setting in which it operates and its ability to perform releva

applicationsarxiv-cs-ai

A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models

arXiv:2607.23439v1 Announce Type: cross Abstract: Graphical models are ubiquitous in social and empirical science as they are intuitive and easy to use. These models belong to the broader class of Mar

A Comparison of Data Augmentation Methods for Training Deep Neural Networks on Synthetic Aperture Sonar

arXiv:2607.23770v1 Announce Type: new Abstract: In this work we study Automatic Target Recognition (ATR) for Synthetic Aperture Sonar (SAS) data with a focus on deep neural networks (DNNs). The main c

applicationsarxiv-cs-lg

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r

A Controlled Visual-Backbone Benchmark for Multimodal Short-Term Solar Irradiance Forecasting

model-releasesarxiv-cs-cv

arXiv:2607.23633v1 Announce Type: cross Abstract: Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and traini

A corrective agentic hybrid RAG and an operations-grounded evaluation for a scientific facility

arXiv:2607.24663v1 Announce Type: cross Abstract: Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, i

A Coulomb Particle Model for Learning Kernel Attention in Transformers

arXiv:2607.23869v1 Announce Type: cross Abstract: Randomized features provide a scalable approximation to kernel machines, but their performance depends strongly on the choice of feature distribution.

A Cyclic Adaptation-Generalization Framework with Uncertainty-Guided Self-Paced Learning for Long-Term Brain-Machine Interfaces

arXiv:2607.24031v1 Announce Type: new Abstract: Brain-Machine Interfaces (BMIs), which link the brain to external devices, hold great potential in rehabilitation, human performance augmentation, and h

A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography

arXiv:2607.22740v1 Announce Type: new Abstract: Weakly supervised pipelines for medical imaging have become increasingly popular over the years. These systems often include multiple stages and compone

Hardware

A didactical-driven teacher assistant for a dimensional modeling course

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

hardwarearxiv-cs-ai

A Few Words Go a Long Way: Language Guided Robot Policy Synthesis

arXiv:2607.23784v1 Announce Type: cross Abstract: While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies tha

A Formal Kinetic Theory for Zeroth-Order Newton Dynamics:Stein-Corrected Hessian Estimation and Curvature--Variance Trade-offs

arXiv:2607.22567v1 Announce Type: cross Abstract: Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-f

A Frozen 12B Beats Frontier Models on Verified Work: 100% Accuracy, 0 Tokens, Bit-Exact, Forever

arXiv:2607.23806v1 Announce Type: cross Abstract: Improving a language model today means retraining it: enormous compute, a new opaque model each cycle, non-deterministic output. We take the opposite

A funny companion: Distinct neural responses to AI- versus human-attributed humor

arXiv:2509.10847v3 Announce Type: replace-cross Abstract: As artificial intelligence (AI) companions become capable of human-like communication, including telling jokes, understanding how people cogni

A General Deep Learning Framework for Wireless Resource Allocation under Discrete Constraints

arXiv:2603.19322v2 Announce Type: replace-cross Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for pr

A Mechanistic Perspective and Circuit-Guided Difficulty Metric for Unlearning

arXiv:2601.09624v2 Announce Type: replace-cross Abstract: Machine unlearning is becoming essential for building trustworthy and compliant language models. Yet unlearning success varies considerably ac

A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection

arXiv:2607.24622v1 Announce Type: cross Abstract: We study imbalanced crowdsourcing with a focus on class-dependent annotator accuracy, a setting that, to the best of our knowledge, remains relatively

applicationsarxiv-cs-lg

A Modern ConvNet for Solar Filament Detection

arXiv:2607.24525v1 Announce Type: cross Abstract: Automated solar filament detection using deep learning faces several challenges. Semantic segmentation of solar filaments is a complicated multiscale

Hardware

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference

arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy

hardwarearxiv-cs-ai

A Multi-stage Constrained Optimization Framework for Data-driven Problems

arXiv:2607.23480v1 Announce Type: new Abstract: Variational autoencoders (VAEs) transform high-dimensional, often noisy data into a compact latent representation, making downstream optimization more t

safetyarxiv-cs-lg

A New Kind of Adversarial Example: Measuring the Human-Model Gap, and Its Relationship to OOD Detection

arXiv:2607.22722v1 Announce Type: cross Abstract: Almost all adversarial attacks add an imperceptible perturbation to fool a model. We instead study the opposite: a large, clearly visible perturbation

A New Role for Relevance: Guiding Corpus Interaction in Agentic Search

arXiv:2607.24223v1 Announce Type: new Abstract: Relevance is a query-dependent estimate of whether a document or excerpt contains useful evidence. Existing retrieval agents use relevance to select top

agentsarxiv-cs-cl

A note on the motion representation and configuration update in time stepping schemes for the constrained rigid body

arXiv:2607.24317v1 Announce Type: new Abstract: The dynamics of a holonomically constrained rigid body can be modeled by Newton-Euler equations subjected to geometric constraints. This is frequently f

researcharxiv-cs-ro

A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions

arXiv:2607.23235v1 Announce Type: new Abstract: Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on ref

A Reference-Free Framework for Evaluating Single-Frame ISP Pipelines

arXiv:2607.23321v1 Announce Type: cross Abstract: Evaluating camera image signal processing (ISP) pipelines requires measuring low-level artifacts introduced by operations such as denoising, demosaici

A Replay-Constrained Simulation Framework for Personalization of Powered Knee--Ankle Prosthesis Controllers

model-releasesarxiv-cs-ro

arXiv:2607.22858v1 Announce Type: new Abstract: Personalization of impedance controllers for powered prosthetic legs is critical to accommodating individual gait biomechanics but remains challenging.

A Resolution of the SS--RS--GD Inequalities

arXiv:2607.22620v1 Announce Type: cross Abstract: Yun, Sra, and Jadbabaie (COLT 2021, open question) conjectured the SS--RS--GD inequalities: for well-conditioned symmetric matrices A_1,ots,A_n, the o

A scalable online machine learning approach for Stock Recommendation

arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e

applicationsarxiv-cs-ai

A Scale-adaptive Vision Model Links C. elegans Neuronal Morphology to Behavior for Neurotoxicity Assessment

model-releasesarxiv-cs-cv

arXiv:2607.23183v1 Announce Type: cross Abstract: Neurological disorders are a leading cause of global disability and are increasingly linked to environmental chemical exposures. Yet neurotoxicity ass

A Simple, Optimal and Efficient Algorithm for Online Exp-Concave Optimization

arXiv:2512.23190v3 Announce Type: replace Abstract: Online eXp-concave Optimization (OXO) is a fundamental problem in online learning, where the goal is to minimize regret when loss functions are expo

A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks

arXiv:2607.23397v1 Announce Type: new Abstract: Hierarchical neural networks are widely used in artificial intelligence, yet their mathematical properties remain incompletely understood. In the infini

A Survey of Graph Transformers: Architectures, Theories and Applications

arXiv:2502.16533v3 Announce Type: replace-cross Abstract: Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph n

A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal

arXiv:2607.24024v1 Announce Type: new Abstract: Stereo matching and surface normal estimation are fundamental tasks in 3D vision. However, existing feed-forward stereo methods still struggle to produc

A Vocabulary for Multi-Agent Automated Research Systems

arXiv:2607.22682v1 Announce Type: new Abstract: We introduce a vocabulary for automated research systems built from one or more agents to make their design choices easier to describe and compare. The

Accuracy Hides How Language Models Fail: Measuring Failure States Under Matched Output Budgets

model-releasesarxiv-cs-cl

arXiv:2607.24268v1 Announce Type: new Abstract: Language-model benchmarks collapse two distinct measurement questions into a single accuracy score: whether a response reached an evaluable state, and w